Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine

doi:10.1109/TVT.2019.2913865

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine
	Zhang, Han 2; Ai, Bo 3; Xu, Wenjun 1; Xu, Li 4; Cui, Shuguang 2
刊名	IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
	2019-07-01
卷号	68 期号:7 页码:7160-7163
关键词	Channel interpolation extreme learning machine tensor decomposition
ISSN号	0018-9545
DOI	10.1109/TVT.2019.2913865
英文摘要	Channel interpolation is an essential technique for providing high-accuracy estimation of the channel state information for wireless systems design where the frequency-space structural correlations of multi-antenna channel are typically hidden in matrix or tensor forms. In this correspondence paper, a modified extreme learning machine (ELM) that can process tensorial data, or ELM model with tensorial inputs (TELM), is proposed to handle the channel interpolation task. The TELM inherits many good properties from ELMs. Based on the TELM, the Tucker decomposed extreme learning machine is proposed for further improving the performance. Furthermore, we establish a theoretical argument to measure the interpolation capability of the proposed learning machines. Experimental results verify that our proposed learning machines can achieve comparable mean squared error (MSE) performance against the traditional ELMs but with 15% shorter running time, and outperform the other methods for a 20% margin measured in MSE for channel interpolation.
资助项目	National Science Foundation[CNS-1824553] ; National Science Foundation[DMS-1622433] ; National Science Foundation[AST-1547436] ; National Science Foundation[ECCS-1659025]
WOS研究方向	Engineering ; Telecommunications ; Transportation
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000476775000077
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/4473]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Cui, Shuguang
作者单位	1.Beijing Univ Posts & Telecommun, Minist Educ, Key Lab Universal Wireless Commun, Beijing 100876, Peoples R China 2.Univ Calif Davis, Dept Elect & Comp Engn, Davis, CA 95616 USA 3.Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Han,Ai, Bo,Xu, Wenjun,et al. Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2019,68(7):7160-7163.
APA	Zhang, Han,Ai, Bo,Xu, Wenjun,Xu, Li,&Cui, Shuguang.(2019).Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine.IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,68(7),7160-7163.
MLA	Zhang, Han,et al."Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine".IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 68.7(2019):7160-7163.